Using fuzzy intervals to represent measurement error and scientific uncertainty in endangered species classification

Although fuzzy numbers (including fuzzy intervals) are often used to capture semantic ambiguity, they are also useful to represent and propagate measurement error. In this application, a classification scheme used by international authorities for assigning biological species into categories of relative endangerment is generalized to accept intervals and triangular or trapezoidal fuzzy numbers as inputs representing empirical estimates of unknown quantities. Non-traditional definitions for fuzzy magnitude comparisons and logical operations were required but, otherwise, standard fuzzy arithmetic was used. A defuzzification step, which explicitly reveals the analyst´s attitudes regarding evidence, can condense the result from the fuzzified classification scheme to a single category. But this step is not required and may be counterproductive